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Fuzzy logic based Unequal Clustering in wireless sensor network for minimizing Energy consumption

机译:基于模糊逻辑的无线传感器网络中的不等聚类,以最大限度地降低能耗

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Energy consumption and lifetime of WSN are the most important research challenges to be resolved. For load balancing and efficient data collection in the network, clustering is used. Sensors in each cluster send the data to their corresponding cluster heads. The cluster head performs data aggregation and transmission of the aggregated data to the base station. Farther sensor nodes data are aggregated by cluster heads and send to the base station. This leads to a heavy traffic and faster depletion of energy to the nodes that are nearer to the sink. To enhance the energy conservation, for suppressing hot spot problem and for load balance achievement, we propose an algorithm namely as ECUCF (Energy Conserved Unequal Clusters with Fuzzy logic). Based on the distances of the nodes from the base station, the network is divided into three different sectors. For designing unequal clusters in each sector, a fuzzy logic approach is followed. The cluster heads that are nearer to the base station are designed to be of smaller sizes whereas the cluster heads that are situated farther away from the sink to have higher cluster sizes. The proposed algorithm ECUCF is simulated using MATLAB environment. The performances obtained are compared with the performances of other clustering schemes like LEACH (equal clustering algorithm) and FBUC (unequal clustering algorithm). From the simulated results, it is found that the performances of ECUCF are much improved as compared to LEACH and FBUC in maximizing the number of clusters, increasing the number of live nodes in the network and extending the lifetime of nodes on each round of operation.
机译:WSN的能源消耗和终身是最重要的研究挑战。对于网络中的负载平衡和高效数据收集,使用群集。每个群集中的传感器将数据发送到相应的群集头部。群集头执行将聚合数据的数据聚合和传输到基站。更远的传感器节点数据由群集头聚合并发送到基站。这导致较为繁忙的交通和更快的能量耗尽到越来越靠近水槽的节点。为了增强节能,为了抑制热点问题和负载平衡成就,我们提出了一种算法,即作为ECUCF(能量保守的模糊逻辑的群集)。基于来自基站节点的距离,网络被分成三个不同的扇区。为了在每个部门设计不等簇,遵循模糊逻辑方法。更靠近基站的簇头被设计为较小的尺寸,而群体头部距离接收器越远越远,则具有更高的聚类尺寸。使用MATLAB环境模拟所提出的算法ECUCF。将获得的性能与其他聚类方案的性能进行比较,如Leach(同等聚类算法)和FBUC(不等聚类算法)。从模拟结果中,发现与LEACH和FBUC相比,与LEACH和FBUC相比,ECUCF的性能大大提高,增加了网络中的实时节点的数量并在每轮操作上扩展节点的寿命。

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